Search results for: food distribution networks

Authors: Firas M. Tuaimah

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This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: short-term load forecasting, artificial neural networks, back propagation learning, hourly load demand

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Authors: Samuel O. Alamu, Seong W. Lee, Blaise Kalmia, Marc J. Louise Caballes, Xuejun Qian

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The application of combustion technologies for thermal conversion of biomass and solid wastes to energy has been a major solution to the effective handling of wastes over a long period of time. Lab-scale biomass combustion systems have been observed to be economically viable and socially acceptable, but major concerns are the environmental impacts of the process and deviation of temperature distribution within the combustion chamber. Both high and low combustion chamber temperature may affect the overall combustion efficiency and gaseous emissions. Therefore, there is an urgent need to develop a control system which measures the deviations of chamber temperature from set target values, sends these deviations (which generates disturbances in the system) in the form of feedback signal (as input), and control operating conditions for correcting the errors. In this research study, major components of the feedback control system were determined, assembled, and tested. In addition, control algorithms were developed to actuate operating conditions (e.g., air velocity, fuel feeding rate) using ladder logic functions embedded in the Programmable Logic Controller (PLC). The developed control algorithm having chamber temperature as a feedback signal is integrated into the lab-scale swirling fluidized bed combustor (SFBC) to investigate the temperature distribution at different heights of the combustion chamber based on various operating conditions. The air blower rates and the fuel feeding rates obtained from automatic control operations were correlated with manual inputs. There was no observable difference in the correlated results, thus indicating that the written PLC program functions were adequate in designing the experimental study of the lab-scale SFBC. The experimental results were analyzed to study the effect of air velocity operating at 222-273 ft/min and fuel feeding rate of 60-90 rpm on the chamber temperature. The developed temperature-based feedback control system was shown to be adequate in controlling the airflow and the fuel feeding rate for the overall biomass combustion process as it helps to minimize the steady-state error.

Keywords: air flow, biomass combustion, feedback control signal, fuel feeding, ladder logic, programmable logic controller, temperature

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Authors: Umar Mujahid, Greatzel Unabia, Hongsik Choi, Binh Tran

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Radio Frequency Identification (RFID) is one of the most commonly used technologies in IoTs and Wireless Sensor Networks which makes the devices identification and tracking extremely easy to manage. Since RFID uses wireless channel for communication, which is open for all types of adversaries, researchers have proposed many Ultralightweight Mutual Authentication Protocols (UMAPs) to ensure security and privacy in a cost-effective manner. These UMAPs involve simple bitwise logical operators such as XOR, AND, OR & Rot, etc., to design the protocol messages. However, most of these UMAPs were later reported to be vulnerable against many malicious attacks. In this paper, we have presented a detailed overview of some eminent UMAPs and also discussed the many security attacks on them. Finally, some recommendations and suggestions have been discussed, which can improve the design of the UMAPs.

Keywords: RFID, Ultralightweight, UMAP, SASI

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Authors: Bhupendra G. Prajapati, Alpesh R. Patel

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The aim of this research work is to develop sustained release multi-particulates dosage form of Dexketoprofen trometamol, which is the pharmacologically active isomer of ketoprofen. The objective is to utilization of active enantiomer with minimal dose and administration frequency, extended release multi-particulates dosage form development for better patience compliance was explored. Drug loaded and sustained release coated pellets were prepared by fluidized bed coating principle by wurster coater. Microcrystalline cellulose as core pellets, povidone as binder and talc as anti-tacking agents were selected during drug loading while Kollicoat SR 30D as sustained release polymer, triethyl citrate as plasticizer and micronized talc as an anti-adherent were used in sustained release coating. Binder optimization trial in drug loading showed that there was increase in process efficiency with increase in the binder concentration. 5 and 7.5%w/w concentration of Povidone K30 with respect to drug amount gave more than 90% process efficiency while higher amount of rejects (agglomerates) were observed for drug layering trial batch taken with 7.5% binder. So for drug loading, optimum Povidone concentration was selected as 5% of drug substance quantity since this trial had good process feasibility and good adhesion of the drug onto the MCC pellets. 2% w/w concentration of talc with respect to total drug layering solid mass shows better anti-tacking property to remove unnecessary static charge as well as agglomeration generation during spraying process. Optimized drug loaded pellets were coated for sustained release coating from 16 to 28% w/w coating to get desired drug release profile and results suggested that 22% w/w coating weight gain is necessary to get the required drug release profile. Three critical process parameters of Wurster coating for sustained release were further statistically optimized for desired quality target product profile attributes like agglomerates formation, process efficiency, and drug release profile using central composite design (CCD) by Minitab software. Results show that derived design space consisting 1.0 to 1.2 bar atomization air pressure, 7.8 to 10.0 gm/min spray rate and 29-34°C product bed temperature gave pre-defined drug product quality attributes. Scanning Image microscopy study results were also dictate that optimized batch pellets had very narrow particle size distribution and smooth surface which were ideal properties for reproducible drug release profile. The study also focused on optimized dexketoprofen trometamol pellets formulation retain its quality attributes while administering with common vehicle, a liquid (water) or semisolid food (apple sauce). Conclusion: Sustained release multi-particulates were successfully developed for dexketoprofen trometamol which may be useful to improve acceptability and palatability of a dosage form for better patient compliance.

Keywords: dexketoprofen trometamol, pellets, fluid bed technology, central composite design

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Authors: Carolina Senabre, Sergio Valero, Miguel Lopez, Antonio Gabaldon

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This paper presents a comprehensive survey of the short-term load forecasting (STLF). Since the behavior of consumers and producers continue changing as new technologies, it is an ongoing process, and moreover, new policies become available. The results of a research study for the Spanish Transport System Operator (REE) is presented in this paper. It is presented the improvement of the forecasting accuracy in the Balearic Islands considering the introduction of meteorological variables, such as temperature to reduce forecasting error. Variables analyzed for the forecasting in terms of overall accuracy are cloudiness, solar radiation, and wind velocity. It has also been analyzed the type of days to be considered in the research.

Keywords: short-term load forecasting, power demand, neural networks, load forecasting

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Authors: Riko Wahyudi, Rezky Lasekti Wicaksono, Ayu Satya Damayanti, Ridhasepta Multi Kenrosa

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Implementing Forest Management Unit (FMU) is considered as the best solution for forest management in developing countries. However, when FMU has been formed, many parties then blame the FMU and assume it is not working on. Currently, there are two main issues that make FMU not be functional i.e. institutional and financial issues. This paper is addressing financial issues to make FMUs in Aceh Province can be functional. A mixed financing scheme is proposed here, both direct and indirect financing. The direct financing scheme derived from two components i.e. public funds and businesses. Non-tax instruments of intergovernmental fiscal transfer (IFT) system and FMU’s businesses are assessed. Meanwhile, indirect financing scheme is conducted by assessing public funds within villages around forest estate as about 50% of total villages in Aceh Province are located surrounding forest estate. Potential instruments under IFT system are forest and mining utilization royalties. In order to make these instruments become direct financing for FMU, interventions on allocation and distribution aspects of them are conducted. In the allocation aspect, alteration in proportion of allocation is required as the authority to manage forest has shifted from district to province. In the distribution aspect, Government of Aceh can earmark usage of the funds for FMUs. International funds for climate change also encouraged to be domesticated and then channeled through these instruments or new instrument under public finance system in Indonesia. Based on FMU’s businesses both from forest products and forest services, FMU can impose non-tax fees for each forest product and service utilization. However, for doing business, the FMU need to be a Public Service Agency (PSA). With this status, FMU can directly utilize the non-tax fees without transferring them to the state treasury. FMU only need to report the fees to Ministry of Finance. Meanwhile, indirect financing scheme is conducted by empowering villages around forest estate as villages in Aceh Province is receiving average village fund of IDR 800 million per village in 2017 and the funds will continue to increase in subsequent years. These schemes should be encouraged in parallel to establish a mixed financing scheme in order to ensure sustainable financing for FMU in Aceh Province, Indonesia.

Keywords: forest management, public funds, mixed financing, village

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Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

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Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: obesity, adult, high in fat, stress, physical activity, consumption pattern

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Authors: Olanrewaju Kafayat, O., Salman Kabir, K.

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The role of organic agriculture in providing food and income is now gaining wider recognition (Van Elzakker et al 2007). The increasing public concerns about food safety issues on the use of fertilizers, pesticide residues, growth hormones, GM organisms, and increasing awareness of environmental quality issues have led to an expanding demand for environmentally friendly products (Thompson, 1998; Rimal et al., 2005). As a result national governments are concerned about diet and health, and there has been renewed recognition of the role of public policy in promoting healthy diets, thus to provide healthier, safer, more confident citizens (Poole et al., 2007), With these benefits, a study into organic vegetables is very vital to all the major stakeholders. This study analyzed the willingness of consumers to pay for organic vegetables in Oyo state, Nigeria. Primary data was collected with the aid of structured questionnaire administered to 168 respondents. These were selected using multistage random sampling. The first stage involved the selection two (2) ADP zones out of the three (3) ADP zones in Oyo state, The second stage involved the random selection of two (2) local government areas each out of the two (2) ADP zones which are; Ibadan South West and Ogbomoso North and random selection of 4 wards each from the local government areas. The third stage involved random selection of 42 household each from of the local government areas. Descriptive statistics, the principal component analysis, and the logistic regression were used to analyze the data. Results showed 55 percent of the respondents were female while 80 percent were  50 years. 74 percent of the respondents agreed that organic vegetables are of better quality. 31 percent of the respondents were aware of organic vegetables as against 69 percent who were not aware. From the logistic model, educational attainment, amount spent on organic vegetables monthly, better quality of organic vegetables and accessibility to organic vegetables were significant and had a positive relationship on willingness to pay for organic vegetable. The variables that were significant and had a negative relationship with WTP are less attractiveness of organic vegetables and household size of the respondents. This study concludes that consumers with higher level of education were more likely to be aware and willing to pay for organic vegetables than those with low levels of education, the study therefore recommends creation of awareness on the relevance of consuming organic vegetables through effective marketing and educational campaigns.

Keywords: consumers awareness, willingness to pay, organic vegetables, Oyo State

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Authors: Aravind Mohan Krishnan

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This paper identifies a research gap in the literature on tourism entrepreneurship in Malawi, Africa, and investigates how entrepreneurs from the Malawian tourism sector discover and exploit business opportunities. In particular, the importance of prior experience and business networks in the opportunity development process is debated. Another area of empirical research examined here is the opportunity recognition-venture creation sequence. While Malawi presents fruitful business opportunities, exploiting these opportunities into fully realized business ideas is a real challenge due to the country’s difficult business environment and poor promotional and marketing efforts. The study concludes by calling for further research in Sub-Saharan Africa in order to develop our understanding of entrepreneurship in this (African) context.

Keywords: entrepreneurship, Malawi, opportunities, tourism

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Authors: Victor Rocha Carvalho

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The Bonner Sphere Spectrometry was used to obtain the average energy, the fluence rate, and radioprotection quantities such as the personal and ambient dose equivalent of the ²⁴¹AmLi and ²⁴¹AmF isotopic neutron sources used in the Neutron Metrology Laboratory - LN. The counts of the sources were performed with six different spherical moderators around the detector. Through this, the neutron spectrum was obtained by means of the software named NeuraLN, developed by the LN, that uses the neural networks technique. The 241AmLi achieved a result close to the literature, and 241AmF, which contains few published references, acquired a result with a slight variation from the literature. Therefore, besides fulfilling its objective, the work raises questions about a possible standard of the ²⁴¹AmLi and about the lack of work with the ²⁴¹AmF.

Keywords: nuclear physics, neutron metrology, neutron spectrometry, bonner sphere spectrometers

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Authors: Sanju Vaidya, Aihua Li

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Vulnerability measures and topological indices are crucial in solving various problems such as the stability of the communication networks and development of mathematical models for chemical compounds. In 1947, Harry Wiener introduced a topological index related to molecular branching. Now there are more than 100 topological indices for graphs. For example, Hosoya polynomials (also called Wiener polynomials) were introduced to derive formulas for certain vulnerability measures and topological indices for various graphs. In this paper, we will find a relation between the Hosoya polynomials of any graph and its Mycielskian graph. Additionally, using this we will compute vulnerability measures, closeness and betweenness centrality, and extended Wiener indices. It is fascinating to see how Hosoya polynomials are useful in the two diverse fields, cybersecurity and chemistry.

Keywords: hosoya polynomial, mycielskian graph, graph vulnerability measure, topological index

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Midhun Xavier

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This paper introduces a method to verify multi-agent systems in industrial control systems using blockchain technology. The proposed solution enables to record and verify each process that occurs while generating a customized product using Ethereum-based smart contracts. Node-Red software agents are developed with the help of semantic web technologies, and these software agents interact with IEC 61499 function blocks to execute the processes. The agent associated with each mechatronic component and its controller can communicate with the blockchain to record various events that occur during each process, and the latter smart contract helps to verify these process orders of the customized product.

Keywords: blockchain, Ethereum, node-red, IEC 61499, multi-agent system, MQTT

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Authors: I.J. Kim, B.C. Kim, J.H. Kim, C.-Y. Yi

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Heat transfer in a graphite calorimeter is analyzed by using the finite elements method. The calorimeter is modeled in 3D geometry. Quasi-adiabatic mode operation is realized in the simulation and the temperature rise by different sources of the ionizing radiation and electric heaters is compared, directly. The temperature distribution caused by the electric power was much different from that by the ionizing radiation because of its point-like localized heating. However, the temperature rise which was finally read by sensing thermistors agreed well to each other within 0.02 %.

Keywords: graphite calorimeter, finite element analysis, heat transfer, quasi-adiabatic mode

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Authors: Stefanie Behncke

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This paper analyses the effects of different macroprudential policy measures that have recently been implemented in Switzerland. Among them is the activation and the increase of the countercyclical capital buffer (CCB) and a tightening of loan-to-value (LTV) requirements. These measures were introduced to limit systemic risks in the Swiss mortgage and real estate markets. They were meant to affect mortgage growth, mortgage risks, and banks’ capital buffers. Evaluation of their quantitative effects provides insights for Swiss policymakers when reassessing their policy. It is also informative for policymakers in other countries who plan to introduce macroprudential instruments. We estimate the effects of the different macroprudential measures with a Differences-in-Differences estimator. Banks differ with respect to the relative importance of mortgages in their portfolio, their riskiness, and their capital buffers. Thus, some of the banks were more affected than others by the CCB, while others were more affected by the LTV requirements. Our analysis is made possible by an unusually informative bank panel data set. It combines data on newly issued mortgage loans and quantitative risk indicators such as LTV and loan-to-income (LTI) ratios with supervisory information on banks’ capital and liquidity situation and balance sheets. Our results suggest that the LTV cap of 90% was most effective. The proportion of new mortgages with a high LTV ratio was significantly reduced. This result does not only apply to the 90% LTV, but also to other threshold values (e.g. 80%, 75%) suggesting that the entire upper part of the LTV distribution was affected. Other outcomes such as the LTI distribution, the growth rates of mortgages and other credits, however, were not significantly affected. Regarding the activation and the increase of the CCB, we do not find any significant effects: neither LTV/LTI risk parameters nor mortgage and other credit growth rates were significantly reduced. This result may reflect that the size of the CCB (1% of relevant residential real estate risk-weighted assets at activation, respectively 2% at the increase) was not sufficiently high enough to trigger a distinct reaction between the banks most likely to be affected by the CCB and those serving as controls. Still, it might be have been effective in increasing the resilience in the overall banking system. From a policy perspective, these results suggest that targeted macroprudential policy measures can contribute to financial stability. In line with findings by others, caps on LTV reduced risk taking in Switzerland. To fully assess the effectiveness of the CCB, further experience is needed.

Keywords: banks, financial stability, macroprudential policy, mortgages

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Authors: Amine Ait-Ouahmed, Didier Josselin, Fen Zhou

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Free-Float car-sharing is an one-way car-sharing service where cars are available anytime and anywhere in the streets such that no dedicated stations are needed. This means that after driving a car you can park it anywhere. This car-sharing system creates an imbalance car distribution in the cites which can be regulated by staff agents through the redistribution of cars. In this paper, we aim to solve the car-reservation and agents traveling problem so that the number of successful cars’ reservations could be maximized. Beside, we also tend to minimize the distance traveled by agents for cars redistribution. To this end, we present a mixed integer linear programming formulation for the car-sharing problem.

Keywords: one-way car-sharing, vehicle redistribution, car reservation, linear programming

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Authors: Joanna Kobus-Cisowska, Daria Szymanowska, Piotr Szulc, Oskar Szczepaniak, Marcin Dziedzinski, Szymon Byczkiewicz

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A wide range of food products is offered on the market. However, increasing consumer awareness of the impact of food on health causes a growing interest in enriched products. Cereal products are an important element of the daily diet of man. In the literature, no data was found on the impact of Morus alba preparations on the content of active ingredients and properties of wholemeal bread. Mulberry leaves (Morus alba L) are a rich source of bioactive compounds with multidirectional antioxidant activity, which means that they can be a component of new foods that prevent disease or support therapy and improve the patient's health. The aim of the study was to assess the impact of the addition of white mulberry leaf extract on the antioxidant activity of bread. It has been shown that bread can be a carrier of biologically active substances from mulberry leaves, because the addition of mulberry at a sensory acceptable level and meeting microbiological requirements significantly influenced the increase in the content of bioactive ingredients and the antioxidant activity of bread. The addition of mulberry leaf water extract to bread increased the level of flavonols and phenolic acids, in particular protocatechic, chlorogenic gallic and caffeic acid and isoquercetin and rutine, and also increased the antioxidant potential, which were microbiological stable during 5 days storage. It has been shown also that the addition of Morus alba preparations has a statistically significant effect on anti-radical activity. In addition, there were no differences in activity in DPPH · and ABTS · + tests between post-storage samples. This means that the compounds responsible for the anti-radical activity present in the bread were not inactivated during storage. It was found that the tested bread was characterized by high microbiological purity, which is indicated by the obtained results of analyzes performed for the titers of indicator microorganisms and the absence of pathogens. In the tested products from the moment of production throughout the entire storage period, no undesirable microflora was found, which proves their safety and guarantees microbiological stability during the storage period.

Keywords: antioxidants, bread, extract, quality

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Authors: Ankit Shai

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CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

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Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Sara Saboonian, Pierre Filion

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The dispersed-suburban model has been the dominant one across North America for the past seventy years, characterized by automobile reliance, low density, and land-use specialization. Two planning models have emerged as possible alternatives to address the ills inflicted by this development pattern. First, there is intensification, which promotes efficient infrastructure by connecting high-density, multi-functional, and walkable nodes with public transit services within the suburban landscape. Second is green infrastructure, which provides environmental health and human well-being by preserving and restoring ecosystem services. This research studies incompatibilities and the possibility of amalgamating the two alternatives in an attempt to develop a comprehensive alternative to suburban model that advocates density, multi-functionality and transit- and pedestrian-conduciveness, with measures capable of mitigating the adverse environmental impacts of compactness. The research investigates three Canadian urban growth centers, where intensification is the current planning practice, and the awareness of green infrastructure benefits is on the rise. However, these three centers are contrasted by their development stage, the presence or absence of protected natural land, their environmental approach, and their adverse environmental consequences according to the planning cannons of different periods. The methods include reviewing the literature on green infrastructure planning, criticizing the Ontario provincial plans for intensification, surveying residents’ preferences for alternative models, and interviewing officials who deal with the local planning for the centers. Moreover, the research draws on recalling debates between New Urbanism and Landscape/Ecological Urbanism. The case studies expose the difficulties in creating urban growth centres that accommodate green infrastructure while adhering to intensification principles. First, the dominant status of intensification and the obstacles confronting intensification have monopolized the planners’ concerns. Second, the tension between green infrastructure and intensification explains the absence of the green infrastructure typologies that correspond to intensification-compatible forms and dynamics. Finally, the lack of highlighted social-economic benefits of green infrastructure reduces residents’ participation. Moreover, the results from the research provide insight into predominating urbanization theories, New Urbanism and Landscape/Ecological Urbanism. In order to understand political, planning, and ecological dynamics of such blending, dexterous context-specific planning is required. Findings suggest the influence of the following factors on amalgamating intensification and green infrastructure. Initially, producing ecosystem services-based justifications for green infrastructure development in the intensification context provides an expert-driven backbone for the implementation programs. This knowledge-base should be translated to effectively imbue different urban stakeholders. Moreover, due to the limited greenfields in intensified areas, spatial distribution and development of multi-level corridors such as pedestrian-hospitable settings and transportation networks along green infrastructure measures are required. Finally, to ensure the long-term integrity of implemented green infrastructure measures, significant investment in public engagement and education, as well as clarification of management responsibilities is essential.

Keywords: ecosystem services, green infrastructure, intensification, planning

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: A. Zapata, Orlando Arroyo, R. Bonett

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Over the last two decades, the growing demand for housing in Latin American countries has led to the development of construction projects based on low and medium-rise buildings with thin reinforced concrete walls. This system, known as Thin Walls Reinforced Concrete Buildings (TWRCB), uses walls with thicknesses from 100 to 150 millimetres, with flexural reinforcement formed by welded wire mesh (WWM) with diameters between 5 and 7 millimetres, arranged in one or two layers. These walls often have irregular structural configurations, including combinations of rectangular shapes. Experimental and numerical research conducted in regions where this structural system is commonplace indicates inherent weaknesses, such as limited ductility due to the WWM reinforcement and thin element dimensions. Because of its complexity, numerical analyses have relied on two-dimensional models that don't explicitly account for the floor system, even though it plays a crucial role in distributing seismic forces among the resilient elements. Nonetheless, the numerical analyses assume a rigid diaphragm hypothesis. For this purpose, two study cases of buildings were selected, low-rise and mid-rise characteristics of TWRCB in Colombia. The buildings were analyzed in Opensees using the MVLEM-3D for walls and shell elements to simulate the slabs to involve the effect of coupling diaphragm in the nonlinear behaviour. Three cases are considered: a) models without a slab, b) models with rigid slabs, and c) models with flexible slabs. An incremental static (pushover) and nonlinear dynamic analyses were carried out using a set of 44 far-field ground motions of the FEMA P-695, scaled to 1.0 and 1.5 factors to consider the probability of collapse for the design base earthquake (DBE) and the maximum considered earthquake (MCE) for the model, according to the location sites and hazard zone of the archetypes in the Colombian NSR-10. Shear base capacity, maximum displacement at the roof, walls shear base individual demands and probabilities of collapse were calculated, to evaluate the effect of absence, rigid and flexible slabs in the nonlinear behaviour of the archetype buildings. The pushover results show that the building exhibits an overstrength between 1.1 to 2 when the slab is considered explicitly and depends on the structural walls plan configuration; additionally, the nonlinear behaviour considering no slab is more conservative than if the slab is represented. Include the flexible slab in the analysis remarks the importance to consider the slab contribution in the shear forces distribution between structural elements according to design resistance and rigidity. The dynamic analysis revealed that including the slab reduces the collapse probability of this system due to have lower displacements and deformations, enhancing the safety of residents and the seismic performance. The strategy of including the slab in modelling is important to capture the real effect on the distribution shear forces in walls due to coupling to estimate the correct nonlinear behaviour in this system and the adequate distribution to proportionate the correct resistance and rigidity of the elements in the design to reduce the possibility of damage to the elements during an earthquake.

Keywords: thin wall reinforced concrete buildings, coupling slab, rigid diaphragm, flexible diaphragm

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Authors: Mohammad Hassan Ramezan zadeh 1 , Majid Seifi 2 , Hoda Hekmat ara 2 1Biomedical Engineering Department, Near East University, Nicosia, Cyprus 2Physics Department, Guilan University , P.O. Box 41335-1914, Rasht, Iran.

Abstract:

Magnetic nano particles of ferric chloride were synthesised using a co-precipitation technique. For the optimal results, ferric chloride at room temperature was added to different surfactant with different ratio of metal ions/surfactant. The samples were characterised using transmission electron microscopy, X-ray diffraction and Fourier transform infrared spectrum to show the presence of nanoparticles, structure and morphology. Magnetic measurements were also carried out on samples using a Vibrating Sample Magnetometer. To show the effect of surfactant on size distribution and crystalline structure of produced nanoparticles, surfactants with various charge such as anionic cetyl trimethyl ammonium bromide (CTAB), cationic sodium dodecyl sulphate (SDS) and neutral TritonX-100 was employed. By changing the surfactant and ratio of metal ions/surfactant the size and crystalline structure of these nanoparticles were controlled. We also show that using anionic stabilizer leads to smallest size and narrowest size distribution and the most crystalline (polycrystalline) structure. In developing our production technique, many parameters were varied. Efforts at reproducing good yields indicated which of the experimental parameters were the most critical and how carefully they had to be controlled. The conditions reported here were the best that we encountered but the range of possible parameter choice is so large that these probably only represent a local optimum. The samples for our chemical process were prepared by adding 0.675 gr ferric chloride (FeCl3, 6H2O) to three different surfactant in water solution. The solution was sonicated for about 30 min until a transparent solution was achieved. Then 0.5 gr sodium hydroxide (NaOH) as a reduction agent was poured to the reaction drop by drop which resulted to participate reddish brown Fe2O3 nanoparticles. After washing with ethanol the obtained powder was calcinated in 600°C for 2h. Here, the sample 1 contained CTAB as a surfactant with ratio of metal ions/surfactant 1/2, sample 2 with CTAB and ratio 1/1, sample 3 with SDS and ratio 1/2, sample 4 SDS 1/1, sample 5 is triton-X-100 with 1/2 and sample 6 triton-X-100 with 1/1.

Keywords: iron oxide nanoparticles, stabilizer, co-precipitation, surfactant

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

Abstract:

Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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Authors: Arunas Burinskas, Aurelija Burinskiene

Abstract:

On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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Authors: Anne Joseph, Yinusa Asiwaju-Bello, Oluwaseun Olabode

Abstract:

Sustainable administration of groundwater resources tapped in Coastal Plain Sands aquifer in Abesan area, Eastern Dahomey Basin, Southwestern Nigeria necessitates the knowledge of the pattern of groundwater flow in meeting a suitable environmental need for habitation. Thirty hand-dug wells were identified and evaluated to study the groundwater flow dynamics and anionic species distribution in the study area. Topography and water table levels method with the aid of Surfer were adopted in the identification of recharge and discharge zones where six recharge and discharge zones were delineated correspondingly. Dissolved anionic species of HCO3-, Cl-, SO42-and NO3- were determined using titrimetric and spectrophotometric method. The trend of significant anionic concentrations of groundwater samples are in the order Cl- > HCO3-> SO42- > NO3-. The prominent anions in the discharge and recharge area are Cl- and HCO3- ranging from 0.22ppm to 3.67ppm and 2.59ppm to 0.72ppm respectively. Analysis of groundwater head distribution and the groundwater flow vector in Abesan area confirmed that Cl- concentration is higher than HCO3- concentration in recharge zones. Conversely, there is a high concentration of HCO3- than Cl- inland towards the continent; therefore, HCO3-concentration in the discharge zones is higher than the Cl- concentration. The anions were to be closely related to the recharge and discharge areas which were confirmed by comparison of activities such as rainfall regime and anthropogenic activities in Abesan area. A large percentage of the samples showed that HCO3-, Cl-, SO42-and NO3- falls within the permissible limit of the W.H.O standard. Most of the samples revealed Cl- / (CO3- + HCO3-) ratio higher than 0.5 indicating that there is saltwater intrusion imprints in the groundwater of the study area. Gibbs plot shown that most of the samples is from rock dominance, some from evaporation dominance and few from precipitation dominance. Potential salinity and SO42/ Cl- ratios signifies that most of the groundwater in Abesan is saline and falls in a water class found to be insuitable for irrigation. Continuous dissolution of these anionic species may pose a significant threat to the inhabitants of Abesan area in the nearest future.

Keywords: Abessan, Anionic species, Discharge, Groundwater flow, Recharge

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Gayathri.G, Hemamalini.A.J, Chandrasekaran.A

Abstract:

Problem statement: Nutritional deficiency, especially calcium, may lead to poor bone formation and mineralization. Although there are plenty of synthetic supplements available, it is essential to make a calcium rich food supplement accessible to combat calcium deficiency that could be readily prepared at the household level. Thus the current study aimed to formulate and standardize an indigenous low-cost calcium-rich food supplement and to study the impact of supplementation on the bone resorption and formation markers. Methods: A Randomized controlled trial was conducted with 60 subjects distributed equally in control and experimental groups, including perimenopausal and postmenopausal women. A plant-based calcium-rich product was developed and supplemented in form of balls as a midmorning and evening snack by addition of optimized proportions of leaves of Sesbania Grandiflora, seeds of Sesamum indicum, Eleusine coracana, Glycine max, Vigna mungo for a period of 6 months. Postmenopausal and perimenopausal women received 1200mg and 800mg of calcium per day from the supplemented, respectively. Outcome measures like serum calcium; betacrosslaps (bone resorption marker) and total P1NP (bone absorption marker) were assessed after 3 months and after 6 months. Results: There were no significant changes seen in the serum calcium and total P1NP levels (bone formation marker) among the subjects during the supplementation period. The bone resorption marker (betacrosslaps) reduced in all the groups and the reduction (0.32 ± 0.130 ng/ml to 0.25 ± 0.130 ng/ml) was found to be statistically highly significant (p < 0.01) in experimental group of perimenopausal subjects and significant (p < 0.05) in experimental group of postmenopausal subjects (1.11 ± 0.290 ng/ml to 0.42 ± 0.263 ng/ml). Conclusion: With the current severe calcium deficiency in the Indian population, integrating low-cost, calcium-rich native foods that could be readily prepared at household level would be useful in raising the nutritional consumption of calcium, which would, in turn, decrease bone turnover.

Keywords: calcium, sesbania grandiflora, sesamum indicum, eleusine coracana, glycine max, vigna mungo, postmenopause, perimenopause, bone resorption, bone absorption, betacrosslaps, total P1NP

Procedia PDF Downloads 136

Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

Abstract:

In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

Procedia PDF Downloads 88